Evolutionary Processes and Systems (EPS) is a project inaugurated in 2012 centered on learning. It teaches students to regard evolution as a learning process — one that can be computationalized, and to reflect better upon their own learning. The learning goal of EPS is to instill upon students a new lens through which they can view complex adaptive systems, including themselves.
At this point, EPS is a blended online learning course. It is designed to help students’ acquire a deeper understanding of evolutionary computation as well as to empower them to think freely and outside the conventional expectations of their learning environment. Its teaching approach involves personal and active interaction among teachers and peers while also engaging digital online learning technology. EPS101@STU has been offered for 3 years at Shantou University, China. It “sandwiches” 10 weeks of online lectures between an introductory and final project week.
EPS teaches an abstracted view of evolution as an adaptive process of improvement dependent upon population-based selection, and replication with variation. It encourages students to recognize evolution in action around them, not only in the conventional context of biology. It illustrates how the evolutionary process guides the emergence and adaptation of intelligent systems. It uses this abstraction of evolution to forge a clear connection to the sort of computation that enables Artificial Intelligence. Students specifically learn about Genetic Algorithms through hands on exercises that evolve software-based strategies that power the intelligent AI players within a simple but engaging digital game called Tron.
This project was supported by Li Ka-Shing foundation September 2012 - May 2015.